autocomplete_model / README.md
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---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: autocomplete_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# autocomplete_model
This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2526
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 17 | 3.2168 |
| No log | 2.0 | 34 | 3.1874 |
| No log | 3.0 | 51 | 3.2537 |
| No log | 4.0 | 68 | 3.2260 |
| No log | 5.0 | 85 | 3.1759 |
| 3.4421 | 6.0 | 102 | 3.1777 |
| 3.4421 | 7.0 | 119 | 3.2093 |
| 3.4421 | 8.0 | 136 | 3.2277 |
| 3.4421 | 9.0 | 153 | 3.1694 |
| 3.4421 | 10.0 | 170 | 3.1333 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3